Method and system for imaging a cell sample

ABSTRACT

The present disclosure provides a method of determining a reference depth level within a cell sample. The method comprises obtaining data representative of a series of images captured by performing a depth scan of the cell sample using a digital microscope, the series of images being associated with a series of depth levels of the cell sample; processing said data for detecting at least one depth level corresponding to a drop in image contrast; and identifying the detected depth level as the reference depth level.

CROSS-REFERENCE TO RELATED APPLICATION

This patent application claims a benefit to the filing date of U.S.Provisional Patent Application Ser. No. 61/826,718 that was filed on May23, 2013. The disclosure of U.S. 61/826,718 is incorporated by referenceherein in its entirety.

TECHNOLOGICAL FIELD

The present disclosure relates to the field of microscopy. Moreparticularly, the present disclosure relates to a system and method forimaging cell samples using a digital microscope.

BACKGROUND

Observation of a sample with a microscope generally requires threedimensional adjustment of focus. Indeed, imaging a specific zone of asample to be investigated (also referred to as investigation zone) mayrequire both alignment of the investigation zone on an optical axis ofthe microscope (also referred to as XY-positioning) and superposition ofthe investigation zone with a focus plane of the microscope (alsoreferred to as Z-positioning). These adjustments may be performedautomatically using an autofocus system cooperating with the microscope.

Autofocus systems relative to the Z-positioning may perform a depthscanning of the sample over a scanning depth interval by varying adistance between the focus plane of the microscope and a movable carrierintended to receive the sample and thereafter compute a focus functionfor the images captured while scanning the sample in depth. Numerousfunctions which are expected to be at a maximum when the image reaches ahighest level of sharpness or contrast have been proposed in theliterature for focusing optical instruments because proper focusintuitively relates to image sharpness and/or contrast. For example,such functions involve determination of standard deviation,absolute-value deviation from a mean, entropy and differentials(gradient or Laplacian) of an image area. FIG. 1 illustrates a typicalfocus curve representing variations of such function with the positionof the focus plane along the Z axis (optical axis) which may be obtainedby carrying out such classical methods on a sample wherein a selectedinvestigation level Z_(inv) is derived by the position corresponding tothe maximum of the function.

GENERAL DESCRIPTION

The Applicant has found a new and useful method and system fordetermining a reference depth level within a cell sample and imaging acell sample.

The present disclosure provides a method of determining a referencedepth level within a cell sample. The method comprises obtaining datarepresentative of a series of images captured by performing a depth scanof the cell sample using a digital microscope, the series of imagesbeing associated with a series of depth levels of the cell sample;processing said data for detecting at least one depth levelcorresponding to a drop in image contrast; and identifying the detecteddepth level as the reference depth level.

In some embodiments, the detected depth level is such that imagecontrast at the detected depth level is lower than image contrastassociated with a depth level immediately preceding the detected depthlevel in the series of depth levels and lower than image contrastassociated with a depth level immediately following the detected depthlevel in the series of depth levels.

In some embodiments, the method further comprises determining a deepnessof the drop in image contrast.

In some embodiments, the method further comprises obtaining datarepresentative of an additional series of images associated with anadditional series of depth levels and a scanning depth interval of theadditional series of images is wider than a scanning depth interval ofthe series of images.

In some embodiments, the method further comprises determining for theseries of images a deepness of the drop in image contrast and theobtaining of data representative of an additional series of images isperformed when the deepness of the drop is below a predetermineddeepness threshold.

In some embodiments, a plurality of drops in image contrast are detectedand the method further comprises identifying the depth levelcorresponding to the deepest drop as the reference depth level.

In some embodiments, processing the series of images comprisescomputing, for each image, a contrast related value enabling to derivethe image contrast of each image.

In some embodiments, the method further comprises calculating imagecontrast using a contrast function increasing with the image contrastand wherein detecting at least one depth level corresponding to a dropin image contrast comprises detecting a well in a contrast curverepresenting image contrast as a function of the depth level.

In some embodiments, the detected depth level corresponds to a bottom ofthe well in the contrast curve.

In some embodiments, the method further comprises determining thedeepness of a well by: determining a right and left boundary depthlevels at which the contrast function becomes inferior to the wellbottom contrast; determining a right and left highest contrast valuesreached by the contrast function between the well bottom depth level andrespectively the right and left boundary depth levels; and calculatingthe minimum of: a difference between the right highest contrast valueand the well bottom contrast and a difference between the left highestcontrast value and the well bottom contrast.

In some embodiments, the method further comprises calculating imagecontrast using a contrast function decreasing with the image contrastand wherein detecting at least one depth level corresponding to a dropin image contrast comprises detecting a roof of a contrast curverepresenting image contrast as a function of the depth level.

In some embodiments, the detected depth level corresponds to a top ofthe roof of the contrast curve.

In some embodiments, the method further comprises determining thedeepness of a roof by: determining a right and left boundary depthlevels at which the contrast function becomes superior to the rooftopcontrast; determining a right and left lowest contrast values reached bythe contrast function between the roof top depth level and respectivelythe right and left boundary depth levels; and calculating the minimumof: the difference between the roof top contrast and the right lowestcontrast value, and the difference between the roof top contrast and theleft lowest contrast value.

In some embodiments, the method further comprises obtaining one or moresupplemental depths levels associated to supplemental contrast values byinterpolating and/or extrapolating the contrast curve and wherein thereference depth level is one of the one or more supplemental depthlevels.

In some embodiments, obtaining the series of images comprises scanning ascanning depth interval of the cell sample using a digital microscope.

In some embodiments, a first scanning depth and a second scanning depthare endpoints of the series of depth levels and the method furthercomprises verifying that a first distance between the reference depthlevel and the first scanning depth and/or a second distance between thereference depth level and the second scanning depth are respectivelyabove a first and/or second predetermined threshold.

In some embodiments, a span of the series of depth levels is of 5 to1000 micrometers.

In some embodiments, a span of the series of depth levels is less than50 micrometers.

In some embodiments, the method further comprises determining anestimated reference depth level and wherein the series of depth levelscovers the estimated reference depth level.

In some embodiments, image contrast is calculated by a contrast functiondecreasing with the image contrast and further comprising transformingthe contrast function into an increasing function of the contrast.

The present disclosure further provides a method of imaging a cellsample using a microscope, comprising: determining a reference depthlevel according to the method previously described; and focusing themicroscope at an investigation level based on the determined referencedepth level.

In some embodiments, the method further comprises capturing one or morefluorescent lighting images of the cell sample.

In some embodiments, focusing the microscope at an investigation levelfurther comprises shifting a focus plane of the digital microscope fromthe reference depth level by a predetermined value.

In some embodiments, the cell sample comprises predominantly red bloodcells.

In some embodiments, the cell sample is essentially a monolayer ofcells.

In some embodiments, the image contrast of an image is calculated fromany of the following contrast functions: variance, standard deviation,sum of absolute-value of derivatives.

The present disclosure provides also an autofocus computation module fora digital microscope. The autofocus computation module comprises: aninput unit configured for receiving from the digital microscope datarepresentative of a series of images captured by performing a depth scanof the cell sample using a digital microscope, the series of imagesbeing associated with a series of depth levels of the cell sample; acalculation unit configured for processing said data for detecting atleast one depth level corresponding to a drop in image contrast andidentifying the detected depth level as the reference depth level; andan output unit for outputting data indicative of the reference depthlevel.

The present disclosure provides also an autofocus system for a digitalmicroscope comprising: an autofocus adaptation module configured forcommanding the digital microscope to vary a distance between a focusplane of the microscope and a sample carrier intended to receive a cellsample for performing a depth scan of the cell sample thereby providinga series of digital images associated with a set of distances betweenthe focus plane and the sample carrier; the autofocus computation modulepreviously described, wherein the input unit is configured for receivingsaid series of digital images and the output unit is configured foroutputting data indicative of the reference depth level to the autofocusadaptation module.

In some embodiments, the autofocus adaptation module is furtherconfigured for commanding the digital microscope to set the focus planeat the reference depth level.

In some embodiments, the autofocus adaptation module is furtherconfigured to set the focus plane at an investigation levelcorresponding to the reference depth level shifted of a predeterminedvalue.

The present disclosure provides also a microscope system comprising: animaging module comprising an optical unit configured for forming amagnified image of a cell sample by conjugating a focus plane and animage plane; and an image sensor unit positioned in the image plane ofthe optical unit; a focus variation module capable of varying a distancebetween the focus plane and a sample carrier intended to receive thecell sample; the autofocus system previously described, the autofocussystem cooperating with the focus variation module and the image sensorunit.

Further, it is understood that the term “well” is used to refer to apoint or a region of a curve where the curve passes from decreasing(curving down) to increasing (curving up). It is understood that theterm well refers to a drop of contrast. In the following, it isgenerally considered that contrast function is such that a drop ofcontrast between two images generates a drop in the contrast functionvalues (i.e. the contrast function is an increasing function of theimage contrast). However, it is noted that if the contrast function is afunction decreasing with the contrast, a drop of contrast would generatean increase in the contrast function thereby turning a “well” into a“roof”. It will be appreciated that a decreasing function can betransformed into an increasing function of the contrast by multiplyingsaid function by −1. Therefore, the present disclosure also applies todecreasing function of the contrast. It will also be appreciated thatanother way of applying the teaching of the present invention to adecreasing function of the contrast would be to determine a “roof”instead of a well for a decreasing contrast function of the contrast(i.e. contrast functions so that a drop of contrast generates anincrease in the contrast function values), wherein the roof refers to apoint or a region of the curve where the curve passes from increasing(curving up) to decreasing (curving down). However, since in the artmost contrast functions are increasing with the contrast, the presentdisclosure refers generally without any limitation to a well.

Furthermore, it is noted that the term “bottom” of the well should beunderstood as the minimum point within a well and that the term “top ofa roof” should be understood as a maximum point within a roof. It isalso understood that the term “series” refers to an ordered set ofvalues. In particular, the series of depth levels may be arranged inincreasing or decreasing order.

It is also appreciated that the present disclosure also applies tofunctions which are usually classified in the art as representative ofsharpness and that the expression “contrast function” should beunderstood as referring generally to contrast and/or sharpness functioni.e. functions for assessing a contrast and/or sharpness of an image.

Furthermore, the term cooperation and its derivatives refer to anoperative connection which may include communication between components.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to better understand the subject matter that is disclosedherein and to exemplify how it may be carried out in practice,embodiments will now be described, by way of non-limiting example only,with reference to the accompanying drawings, in which:

FIG. 1, already described, illustrates a focus curve for determining aninvestigation level according to the prior art;

FIG. 2 is a flow chart illustrating steps of a method of imaging a cellsample according to some embodiments of the present disclosure;

FIG. 3 illustrates an image variance calculation according to someembodiments of the present disclosure;

FIG. 4 illustrates schematically a red blood cell under investigationaccording to some embodiments of the present disclosure;

FIG. 5 illustrates a focus curve obtained by depth scanning of a cellsample and computing of a focus function according to some embodimentsof the present disclosure; and

FIG. 6 is a diagram illustrating a system according to some embodimentsof the present disclosure.

DETAILED DESCRIPTION OF EMBODIMENTS

In the following detailed description, numerous specific details are setforth in order to provide a thorough understanding of the invention.However, it will be understood by those skilled in the art that thepresent invention may be practiced without these specific details. Inother instances, well-known features, structures, characteristics,stages, methods, procedures, modules, components and systems, have notbeen described in detail so as not to obscure the present invention.

Unless specifically stated otherwise, as apparent from the followingdiscussions, it is appreciated that throughout the specificationdiscussions utilizing terms such as “processing”, “calculating”,“computing”, “determining”, “generating”, “configuring”, “selecting”,“defining”, or the like, include action and/or processes of a computerthat manipulate and/or transform data into other data, said datarepresented as physical quantities, e.g. such as electronic quantities,and/or said data representing the physical objects. The terms “computer”and “processor” should be expansively construed to cover any kind ofelectronic device with data processing capabilities.

The operations in accordance with the teachings herein may be performedby a computer specially constructed for the desired purposes or by ageneral purpose computer specially configured for the desired purpose bya computer program stored in a non-transitory computer readable storagemedium. The term “non-transitory” is used herein to exclude transitory,propagating signals, but to otherwise include any volatile ornon-volatile computer memory technology suitable to the application.

As used herein, the phrase “for example,” “such as”, “for instance” andvariants thereof describe non-limiting embodiments of the presentlydisclosed subject matter. Reference in the specification to “one case”,“some cases”, “other cases” or variants thereof means that a particularfeature, structure or characteristic described in connection with theembodiment(s) is included in at least one embodiment of the presentlydisclosed subject matter. Thus the appearance of the phrase “one case”,“some cases”, “other cases” or variants thereof does not necessarilyrefer to the same embodiment(s).

It is appreciated that, unless specifically stated otherwise, certainfeatures of the presently disclosed subject matter, which are, forclarity, described in the context of separate embodiments, may also beprovided in combination in a single embodiment. Conversely, variousfeatures of the presently disclosed subject matter, which are, forbrevity, described in the context of a single embodiment, may also beprovided separately or in any suitable sub-combination.

FIG. 2 illustrates generally steps of a method of imaging a cell sampleaccording to some embodiments of the present disclosure. The imagingmethod includes in a first stage, a method of determining a referencedepth level within a cell sample and, in a second stage, focusing adigital microscope at an investigation level derived from the depthreference level. The method of determining a reference depth level maybe carried out on a computing module. Advantageously, the computingmodule may belong to an autofocus system of the microscope. The step offocusing the microscope may be performed automatically upon command bythe autofocus system. The cell sample may comprise red blood cells andmay optionally be a cell monolayer comprising red blood cells.

In 100, a series of images (also referred to as a set of images)representative of light captured by focusing a digital microscope at acorresponding series of depths levels within the cell sample isobtained. It is understood that the term “obtain data representative ofa series of images” encompasses both actual imaging of the cell sampleto acquire the set of images (in-depth scanning) and respective data,and also loading/downloading from a computer storage media the datarelating to a set of images preliminarily acquired by a digitalmicroscope. In some embodiments, obtaining depth scan images comprisesin-depth scanning of the cell sample with a digital microscope andobtaining the set of images can be carried out using an image sensorunit of the microscope connected with a computing module so as toprovide the in-depth images (i.e. images captured during in-depthscanning) to the computing module. In some embodiments, in-depthscanning may be performed with brightfield illumination.

The set (series) of images may be understood as a series of slices ofthe cell sample corresponding to different positions along the Z axis(optical axis of the microscope). Each image may be associated with adepth level. Optionally one or more images are associated with depthlevels within the cell sample that are above or below the cells in cellsample. Optionally one or more images are associated with depth levelsthat are above or below the cell sample. The set of images may resultfrom an in-depth scanning of the cell sample. Such in-depth scanning mayfor example be carried out by varying a distance between a focus planeof the microscope and a sample carrier intended to accommodate the cellsample by methods well known in the art.

Further, the term depth level may be understood as a coordinate valuealong the optical axis of the microscope corresponding to a positionthat is optionally inside the cell sample. The actual direction of theaxis and the origin of the axis to quantify depth may be arbitrarilychosen. The images may be obtained at any order, and may have an equaldistance along the axis between pairs of consequent images or at avarying distance i.e. the in-depth scanning may be performed with afixed step or with a variable step. For example, the origin of the axismay be positioned at an outer surface of the cell sample facing anobjective of the microscope and the direction of the coordinate axis maybe chosen so that the coordinates increase when progressing toward thecell sample. It is also understood that since the series of depth levelsmay be understood as an ordered set along the axis, it is possible todefine endpoint depth levels (hereinafter referred to as endpoints) ofthe series of depth levels. In the following, the term scanning depthinterval refers to a series of depth levels between two endpoints' depthlevels. One endpoint level of a series of depth levels, for example aminimum depth level of the set, may be referred to as a first scanningdepth levels and the other endpoint of the set, for example the maximumdepth level, may be referred to as a second scanning depth level. Insuch case, the scanning depth interval refers to the depth levelscomprised between the first and second scanning depth levels.

In some embodiments, an estimated reference depth level may bepreliminarily provided. For example, the cell sample may comprise aplurality of fields to be investigated and reference depth levelsdetermined for one or more previous fields may be used to estimate theestimated reference level for a subsequent field. In these embodiments,the scanning depth interval may be selected so as to cover the estimateddepth reference level i.e. distances between the estimated depthreference level and the first and second scanning depth levels may beabove a predetermined threshold. In some embodiments, a span of thedepth scanning interval may be of around 5 micrometers to 1000micrometers. In some embodiments, the span of the depth scanninginterval may be between 150 and 250 micrometer, or less than 50micrometers or even between 10 and 30 micrometers. Optionally, theestimated depth level is approximately in the midpoint of the span ofthe depth scanning interval.

In 200, the series of images and associated depth levels (or the datarepresentative thereof) are processed for detecting at least one depthlevel corresponding to a drop in image contrast and the detected depthlevel is identified to be the reference depth level. The detected depthlevel may be such that an image contrast at the detected depth level islower than the image contrast at immediately preceding and following thereference depth level (i.e. adjacent depth levels) in the series ofdepth levels. The drop in image contrast may be understood as a drop ofimage contrast over depth level (i.e. as a function of depth level). Itis noted that when the contrast function used to calculate the imagecontrast is increasing with the contrast, 200 may be carried out by todetecting a well of a contrast curve representing image contrast as afunction of depth level. Image contrast of an image may be provided byapplying a contrast function to the image. A well is considered to beformed on the contrast curve when a contrast function value is inferiorat least to the previous and subsequent adjacent contrast functionvalues. In the following, some embodiments are described in which theimage contrast is provided by the calculation of variance. It isunderstood that other functions can be contemplated to determine thecontrast of an image. The set of images associated with the series ofdepth levels within the cell sample enables to analyze variations of animage parameter as a function of the depth level. In some embodiments,image variance may be computed for every image of the set of obtainedimages.

FIG. 3 illustrates image variance calculation on an example image Icomprising n*p pixels (n, p integers) of pixel intensity I_(i,j) wherein1≤i≤n and 1≤j≤p. The variance can be expressed as follows:Var(I)=E[(I _(i,j) −E(I))²],

wherein E(I) is the mean value of the pixel intensity I_(i,j) over theexample image.

In some embodiments, a variance related value may be computed for eachimage of the set of images. It is understood that the variance relatedvalue encompasses transformations of the image variance enabling toderive the image variance i.e. transformations equivalent to imagevariance calculation, for example standard deviation.

As explained above, the reference depth level may correspond to aminimum point within a well of the contrast curve (i.e. a local drop ofcontrast). The contrast curve may be defined as a curve representing thevalues of the contrast function (for example image variance) as afunction of the Z-coordinate of the focus plane during the depthscanning. In some embodiments, the reference depth level may correspondto the Z-position of a minimum point within a deepest well of thecontrast curve. As explained above, a well may also be defined as apoint where the curve passes from decreasing to increasing. Theprocessing for deriving the reference depth level may comprise detectingone or more minimum points within wells i.e. points of the contrastcurve at which the contrast function value is inferior to both adjacentpoints i.e. the minimum point within the well is below the contrastfunction value of the previous and subsequent points.

The deepness of the well may also be determined for example in order tofind the deepest well of the contrast curve or in order to proceed toanother depth scan if the deepness of all the identified wells of thecontrast curve are below a minimal deepness threshold.

Determining a deepness of a well may comprise determining the height ofat least one wall of the well. In some embodiments, the height of a wallmay be defined as the absolute value of a difference between thecontrast function value at the minimum point within the well (wellcontrast value) and the contrast function value at the aperture of thewell (or maximum point at the aperture of the well). The aperture of thewell may be detected by comparing subsequent values of the focusfunction.

In some other embodiments, determining the deepness of the well maycomprise (1) determining a right and left boundary depth levels at whichthe contrast function value becomes inferior to the well contrast value;(2) determining a right and left highest contrast function valuesreached by the focus function between the well depth level andrespectively the right and left boundary depth levels and (3)calculating the minimum of the differences between the well contrastvalue and the right and left highest variance values, wherein theminimum is the deepness of the well. These embodiments can be regardedas basing the deepness of a well on the minimum amount needed to beclimbed over the contrast curve to reach a lower contrast function valuethan the contrast function value at the considered well (well bottomcontrast).

In some embodiments, the processing may further comprise a verificationstep comprising verifying that the deepness of the deepest detected wellis above a predetermined threshold and may further include repeating thein-depth scanning with a wider span if the deepness of the deepest wellis below said threshold.

In some cases, several local minima (wells) may be found for a set ofimages, in which case one of the minima is selected to define thereference depth level. Optionally this is performed as follows: Thevariance value for each minimum is compared with the variance values ofadjacent portions of the curve, for example within a comparison range of±5 micrometers from the depth level associated with the minimum. Basedon this comparison, each minimum is associated with a “variance deepnessvalue”. The variance deepness value is a function (e.g. ratio) betweenthe variance value of the minimum point and the highest variance valueassociated any point of the curve within the comparison range. In theexample shown in FIG. 5, the variance value of the minimum point 37 isV₃₇, and the variance deepness value is a function of V₃₇ and thevariance value V₃₈ that is associated with the high point 38 (e.g. thevariance deepness value equals V₃₇/V₃₈). Optionally, the reference pointis defined as the minimum having the lowest variance deepness value.

If the comparison range comprises a low point that has a variance valuethat is equal to or lower than that of the local minimum for which avariance deepness value is calculated, the highest point that will beused for this calculation may be the highest point between the localminimum and the nearest additional low point in the comparison range.

Optionally, the variance deepness value must exceed a predeterminedthreshold for a local minimum to be selected. For example, if no minimumis found having a variance deepness value that is 0.9 or less, or even0.8 or less, no reference depth level is defined. In such cases, 100 maybe repeated such that a new series of depth scan images is obtained anda new minimum is found. Optionally, the first series of depth scanimages corresponds with a first scanning depth interval and the secondset of images corresponds with a second scanning depth interval beingdifferent than the first scanning depth interval. Optionally, the secondscanning depth interval is larger than the first scanning depthinterval. Optionally both the first and second scanning depth intervalscover the estimated reference depth level. Optionally the first scanningdepth interval spans less than 50 micrometers, for example between 10and 30 micrometers. Optionally, the second scanning depth intervalsspans between 100 and 1000 micrometers, for example between 150 and 250micrometers.

In a variant, detection of the depth reference level may be performed bysearching for a lower bound of the contrast function on a restricteddepth level interval. For example, the restricted interval may exclude aregion near the endpoints of the depth scanning interval. Further, theprocessing may comprise detecting whether the depth reference level issufficiently distant from the endpoints of the depth scanning interval.In some embodiments, detection of the reference depth level may compriseidentifying two maxima depth levels at which the focus function reachesmaxima (or roofs). In some embodiments, the two maxima may be detectedas the points where the contrast function passes from increasing todecreasing. The reference depth level may be detected by searching forthe lower bound of the focus function on the restricted intervalconsisting of the depth levels between the two identified maxima depthlevels.

The well (or deepest well) may be reached for a given depth level of theseries of depth levels. Alternatively, the reference depth level may beextrapolated or interpolated from the series of depth levels andassociated images. For example, in a preliminary step, supplementalpoints may be interpolated and/or extrapolated on the contrast curve andone of these supplemental points may correspond to the well (or deepestwell) of the contrast curve. For example, the supplemental points may beinterpolated as being in-between two depth levels of the series of depthlevels.

It is understood that implementation of the present disclosure does notrequire generation of the actual curve representing the variation of thecontrast function over depth level but that a search for an well (or aroof if the contrast function is decreasing with the contrast) can beperformed mathematically using the image representative data

In some embodiments, the cell sample may comprise predominantly redblood cells. In some embodiments, the cell sample may essentially be amonolayer of cells, wherein at least 80% of the cells or even at least90% of the cells have direct contact with the surface on which the cellsample is held. In the context of imaging blood samples, the Applicanthas found that the proposed method based on determining a referencedepth level corresponding to a minimum of variance (contrast and/orsharpness) over the in-depth scanning may be particularly advantageous.

Indeed, the proposed method can be performed using brightfieldillumination and provide with appropriate results for furtherinvestigation using fluorescent illumination. This may lead to reducingfocus time because performing focus on fluorescent images is typicallyslower than when using brightfield, since obtaining fluorescent imagestypically requires longer exposure periods. Further, obtainingfluorescent images for focusing purpose may be problematic becausefluorescent imaging is known to degrade the fluorescent response of thesample due to photo-bleaching.

In brightfield illumination of blood samples, the most visibly abundantobject is generally red blood cells. Healthy red blood cells arecharacterized by a distinctive biconcave shape as schematicallyillustrated by FIG. 4 in which a blood cell 25 is depicted. Blood cell25 may be characterized as having a midplane 27. The Applyingcontrast-based functions and/or sharpness based functions to brightfieldmicroscopy of a blood sample containing mostly red blood cells (forexample a blood sample) may yield graphs qualitatively similar to thatshown in FIG. 5. FIG. 5 illustrates a curve representing variations ofimage variance (image contrast) over scanning depth level. The curvenotably comprises a well 37 embraced between two maxima 38, 39 (in thisexample a saddle point which is a local minimum, but not an absoluteone).

The Applicant found that the depth level corresponding to the well 37provides an efficient reference level providing robust and consistentresults across different microscope hardware including different formsof brightfield illumination and different forms of sample preparation(dry thin smears, wet smears and microfluidic preparation). Moreover, afocus position based on the well 37 position provides a baseline forepifluorescent imaging. The Applicant contemplates that the two maxima38, 39 may be correlated to the bottom and top convex part 28, 29 of theblood cell previously illustrated on FIG. 4 and the well 37 (which isalso a local minimum) may be correlated to the midplane 27.

Therefore, imaging at the reference depth level or in its vicinity mayprovide efficient parasite detection. The Applicant further found thatthe consistency of the focus generated by the proposed method ofdetermining a minimum of the contrast function may be explained asfollows: the maxima 38, 39 surrounding the well 37 typically fall within1 micrometer of each other. Consequently, the well 37 is steep therebycausing discernible shifts in the contrast function even for shifts ofdepth level of about a tenth of a micron. It is appreciated that havinga consistent reference level within a cell sample enables to establishreliable automated diagnosis.

In 300 of FIG. 2, the digital microscope may be focused at aninvestigation level based on the determined reference level. In someembodiments, the investigation level may be equal to the referencelevel. In some embodiments, the investigation level may be shifted by apredetermined value with respect to the reference level. For example,this value may be in the range of 0.2-3 micrometers, or about 1-2micrometers or about 1.5 micrometer. In some embodiments, switching toan investigation level that is different than the reference depth valueenables to increase the contrast and/or sharpness of the image whilepreserving the consistency provided by the aforementioned method ofdetermining a reference depth level. As explained above, focusing themicroscope at the investigation level may enable to investigate the cellsample. In some embodiments, the investigation may be carried out withfluorescent illumination and/or with brightfield illumination. In someembodiments, the investigation level will provide a sharp image (or eventhe sharpest and/or highest contrast image).

FIG. 6 illustrates a microscope system 1 for investigating a cell sample2 in some embodiments of the present disclosure adapted to carry out themethods previously described. The microscope system 1 may comprise animaging module 10, a focus variation module 20, a sample carrier 30 andan autofocus system 40.

The imaging module 10 may comprise an optical unit 11 and an imagesensor unit 12. Optical unit 11 may be configured for forming amagnified image of a sample (for example cell sample 2) by conjugating afocus plane 111 and an image plane. The image sensor unit 12 maycomprise an image sensor, for example a charge-coupled-device (CCD),complementary metal-oxide-semiconductor (CMOS) sensor, matrix sensor,positioned in the image plane of the optical unit 11 so as to sense themagnified image. The sensor image unit 11 may output digital imagesacquired to a screen display (not shown) and/or to the autofocus system40.

The focus variation module 20 may be configured to vary a distancebetween the focus plane 111 of the optical unit 11 and the samplecarrier 30. The focus variation module 20 may be operated manually orautomatically via a mechanical interface which may for example modifythe position of the sample carrier 30 along an optical axis Z of theoptical unit 11. Further, the focus variation module 20 may be commandedby the autofocus system 40. For example, the focus variation module 20may vary the distance between the sample carrier 30 and the focus planeby (1) modifying the position of the optical unit 11 along the opticalaxis Z, (2) modifying the position of the sample carrier 30 along theposition of the optical axis Z, (3) modifying the position of the focusplane by for example changing a focal length of the optical unit 11, ora combination thereof:

The sample carrier 30 may comprise a plate or stage. The sample carrier30 may be configured to accommodate the cell sample 2. The carrier maybe any carrier known in the art for holding a biological sample.Optionally, the bottom surface of the carrier is essentially flat, toallow cells in contact therewith to be at about the same distance fromthe focal plane of the microscope. Examples include carrier slides,laboratory receptacles, dishes, plates, multi-well plates, test tubes(e.g. with a flat bottom), microfluidic cells and cartridges and thelike.

Autofocus system 40 may comprise an autofocus computation module 41 andan autofocus adaption module 42. The autofocus computation module may beconnected to the image sensor module 12 so as to receive images acquiredby the imaging module 10. The autofocus adaptation module may beconnected to the focus variation module 20 so as to be capable ofcommanding the focus variation module 20.

The autofocus adaptation module 42 may be configured for commanding adepth scanning of the cell sample 2. In order to do so, the autofocusadaptation module 42 may be configured for commanding the focusvariation module 20 to set the focus plane of the optical unit 11 at aseries of depth levels within the cell sample 2 so as to perform thedepth scanning of the cell sample 2 between a first scanning depth level201 and a second scanning depth level 202. Further, upon output of thereference depth level by the autofocus computing module 41, theautofocus adaptation module 42 may be further configured for commandingthe focus variation module 20 to set the focus plane of the optical unit11 at an investigation depth level. The investigation depth level may bethe reference depth level or may be derived by shifting of apredetermined value the reference depth level.

The autofocus computation module 41 may be configured for implementingthe method of determining a reference depth level described hereinaboveand to output the reference depth level to the autofocus adaptationmodule 42. The autofocus computation module may comprise an input unitconfigured for receiving the set of in-depth images from the imagesensor unit 12; a calculation unit configured for processing the set ofimages to derive a reference depth level corresponding to a well of acontrast curve representing an image contrast function of the depthlevel; and an output unit configured for outputting data indicative ofthe reference depth level. Upon receipt of the depth scan images by theimage sensor unit 12, the calculation unit may process the set of imagesto derive the reference depth level. The image contrast may be definedby image variance or by other functions representative of the contrastand/or the sharpness of an image as described above. The determinationof the reference depth level at which the image contrast drops (is at aminimum value within a well) may include computing for each depth scanimage an image variance (or an image variance related value).

While certain features of the invention have been illustrated anddescribed herein, many modifications, substitutions, changes, andequivalents will now occur to those of ordinary skill in the art. It is,therefore, to be understood that the appended claims are intended tocover all such modifications and changes as fall within the true spiritof the invention. It will be appreciated that the embodiments describedabove are cited by way of example, and various features thereof andcombinations of these features can be varied and modified.

While various embodiments have been shown and described, it will beunderstood that there is no intent to limit the invention by suchdisclosure, but rather, it is intended to cover all modifications andalternate constructions falling within the scope of the invention, asdefined in the appended claims.

The invention claimed is:
 1. A method for use with a cell sample, themethod comprising: obtaining data representative of a series of imagescaptured by performing a depth scan of the cell sample using amicroscope, the series of images being associated with a series of depthlevels of the cell sample; identifying one of the depth levels as beingan optimum focal plane for imaging one or more entities within thesample using the microscope, by: detecting a plurality of depth levelsas corresponding to drops in image contrast; identifying one of theplurality of detected depth levels as corresponding to a deepest drop inimage contrast; and identifying the depth level that corresponds to thedeepest drop in image contrast as the depth level that is the optimumfocal plane; and imaging the cell sample using the microscope, byfocusing the microscope at an investigative depth level that is based onthe identified depth level.
 2. The method according to claim 1, whereinidentifying one of the depth levels as the optimum focal plane comprisesidentifying that the identified depth level is such that image contrastat the identified depth level is lower than image contrast associatedwith a depth level immediately preceding the identified depth level inthe series of depth levels and lower than image contrast associated witha depth level immediately following the identified depth level in theseries of depth levels.
 3. The method according to claim 1, furthercomprising obtaining data representative of an additional series ofimages associated with an additional series of depth levels, wherein ascanning depth interval of the additional series of images is wider thana scanning depth interval of the series of images.
 4. The method ofclaim 3, wherein the obtaining of the data representative of theadditional series of images is performed in response to the deepness ofthe drop in image contrast at the identified depth level being below apredetermined deepness threshold.
 5. The method according to claim 1,wherein detecting the plurality of depth levels as corresponding todrops in image contrast comprises computing, for each image, a contrastrelated value that enables derivation of an image contrast for eachimage.
 6. The method according to claim 1, wherein detecting theplurality of depth levels as corresponding to drops in image contrastcomprises calculating image contrast as a function of depth level usinga contrast function that increases with image contrast, and detectingone or more wells in a contrast curve representing the image contrast asthe function of depth level.
 7. The method according to claim 6, whereinidentifying one of the depth levels as corresponding to the deepest dropin image contrast comprises detecting that the depth level correspondsto a bottom of one of the wells in the contrast curve.
 8. The methodaccording to claim 6, wherein identifying one of the depth levels ascorresponding to the deepest drop in image contrast comprisesdetermining a deepness of the well corresponding to that depth level by:determining right and left boundary depth levels at which the contrastfunction becomes inferior to the well bottom contrast; determining rightand left highest contrast values reached by the contrast functionbetween the well bottom depth level and respectively the right and leftboundary depth levels; and calculating a minimum of: a differencebetween the right highest contrast value and the well bottom contrast;and a difference between the left highest contrast value and the wellbottom contrast.
 9. The method according to claim 1, wherein detectingthe plurality of depth levels as corresponding to drops in imagecontrast comprises calculating image contrast as a function of depthlevel using a contrast function that decreases with image contrast anddetecting one or more roofs of a contrast curve representing the imagecontrast as the function of depth level.
 10. The method according toclaim 9, wherein identifying one of the depth levels as corresponding tothe deepest in image contrast comprises detecting that the depth levelcorresponds to a top of one of the roofs of the contrast curve.
 11. Themethod according to claim 9, wherein identifying one of the depth levelsas corresponding to the deepest drop in image contrast comprisesdetermining a deepness of the roof corresponding to that depth level by:determining right and left boundary depth levels at which the contrastfunction becomes superior to the rooftop contrast; determining right andleft lowest contrast values reached by the contrast function between theroof top depth level and respectively the right and left boundary depthlevels; and calculating a minimum of: a difference between the roof topcontrast and the right lowest contrast value, and a difference betweenthe roof top contrast and the left lowest contrast value.
 12. The methodaccording to claim 1, wherein detecting that the plurality of depthlevels as corresponding to drops in image contrast comprises:calculating image contrast as a function of depth level, generating acontrast curve representing the image contrast as the function of depthlevel, and obtaining one or more supplemental depths levels associatedto supplemental contrast values by interpolating or extrapolating thecontrast curve; and wherein identifying the depth level that is at theoptimal focal plane comprises identifying, as the depth level that is atthe optimum focal plane, one of the one or more supplemental depthlevels.
 13. The method according to claim 1, wherein obtaining datarepresentative of the series of images comprises scanning a scanningdepth interval of the cell sample using the microscope.
 14. The methodaccording to claim 1, wherein the series of images are associated with afirst scanning depth and a second scanning depth that are endpoints ofthe series of depth levels and the method further comprises verifying atleast one of: a first distance between the optimum focal plane and thefirst scanning depth being above a first predetermined threshold, and asecond distance between the optimum focal plane and the second scanningdepth being above a second predetermined threshold.
 15. The methodaccording to claim 1, wherein obtaining the data representative of theseries of images comprises obtaining data representative of a series ofimages captured by performing a depth scan of the cell sample using themicroscope, the series of images being associated with a series of depthlevels of the cell sample, a span of the series of depth levels being 5to 1000 micrometers.
 16. The method according to claim 1, whereinobtaining the data representative of the series of images comprisesobtaining data representative of a series of images captured byperforming a depth scan of the cell sample using the microscope, theseries of images being associated with a series of depth levels of thecell sample, a span of the series of depth levels being less than 50micrometers.
 17. The method according to claim 1, further comprisingdetermining an estimated optimum focal plane and wherein obtaining thedata representative of the series of images comprises obtaining datarepresentative of a series of images captured by performing a depth scanof the cell sample using the microscope, the series of images beingassociated with a series of depth levels that covers the estimatedoptimum focal plane.
 18. The method according to claim 1, whereinfocusing the microscope at the investigative depth level furthercomprises shifting a focus plane of the microscope from the identifieddepth level by a predetermined value.
 19. The method according to claim1, wherein the cell sample includes predominantly red blood cells, andobtaining data representative of the series of images captured byperforming the depth scan of the cell sample comprises obtaining datarepresentative of a series of images captured by performing a depth scanof the cell sample that includes predominantly red blood cells using themicroscope.
 20. The method according to claim 1, wherein the cell sampleis essentially a monolayer of cells, and obtaining data representativeof the series of images captured by performing the depth scan of thecell sample comprises obtaining data representative of a series ofimages captured by performing a depth scan of the cell sample that isessentially a monolayer of cells using the microscope.
 21. The methodaccording to claim 1, wherein detecting the plurality of depth levels ascorresponding to drops in image contrast comprises calculating imagecontrast using a contrast function selected from the group consistingof: variance, standard deviation, and sum of absolute-value ofderivatives.
 22. The method according to claim 1, wherein identifyingone of the depth levels as the optimum focal plane comprises:determining a variance deepness value associated with the depth level,the variance deepness value being a function of a variance-related valueof the depth level, and a maximum of variance-related values associatedwith depth levels that are within a given range of distances from thedepth level, and identifying the depth level as the depth level that isat the optimum focal plane at least partially based upon the variancedeepness value associated with the depth level.
 23. The method accordingto claim 1, wherein identifying one of the depth levels as the optimumfocal plane comprises determining image variance values for depth levelswithin a given range of distances from the depth level.
 24. The methodaccording to claim 1, wherein: obtaining data representative of theseries of images captured by performing the depth scan of the cellsample using the microscope comprises obtaining data representative of aseries of images captured by performing a depth scan of the cell sampleusing the microscope, under a first illumination condition; identifyingone of the depth levels as being the optimum focal plane for imaging theone or more entities within the sample using the microscope comprisesidentifying one of the depth levels as being an optimum focal plane forimaging the one or more entities within the sample using the microscope,under the first illumination condition; and imaging the cell sampleusing the microscope comprises imaging the cell sample under a secondillumination condition that is different from the first illuminationcondition, using the microscope, by focusing the microscope at aninvestigative depth level that is based on the identified depth level.25. The method according to claim 24, wherein: obtaining datarepresentative of the series of images captured by performing the depthscan of the cell sample using the microscope comprises obtaining datarepresentative of a series of images captured by performing a depth scanof the cell sample using the microscope, under brightfield illuminationconditions; identifying one of the depth levels as being the optimumfocal plane for imaging the one or more entities within the sample usingthe microscope comprises identifying one of the depth levels as being anoptimum focal plane for imaging the one or more entities within thesample using the microscope, under the brightfield illuminationconditions; and imaging the cell sample using the microscope comprisesimaging the cell sample under fluorescent lighting conditions, using themicroscope, by focusing the microscope at an investigative depth levelthat is based on the identified depth level.
 26. The method according toclaim 24, wherein: obtaining data representative of the series of imagescaptured by performing the depth scan of the cell sample using themicroscope comprises obtaining data representative of a series of imagescaptured by performing a depth scan of the cell sample using themicroscope, under a first brightfield illumination condition;identifying one of the depth levels as being the optimum focal plane forimaging the one or more entities within the sample using the microscopecomprises identifying one of the depth levels as being an optimum focalplane for imaging the one or more entities within the sample using themicroscope, under the first brightfield illumination condition; andimaging the cell sample using the microscope comprises imaging the cellsample under a second brightfield illumination condition that isdifferent from the first brightfield illumination condition, using themicroscope, by focusing the microscope at an investigative depth levelthat is based on the identified depth level.
 27. An autofocuscomputation module for use with a digital microscope, the autofocuscomputation module comprising: an input unit configured for receivingfrom the digital microscope data representative of a series of imagescaptured by performing a depth scan of the cell sample using the digitalmicroscope, the series of images being associated with a series of depthlevels of the cell sample; a calculation unit configured for identifyingone of the depth levels as being an optimum focal plane for imaging oneor more entities within the sample using the microscope, by: detecting aplurality of depth levels as corresponding to drops in image contrast;identifying one of the plurality of detected depth levels ascorresponding to a deepest drop in image contrast; and identifying thedepth level that corresponds to the deepest drop in image contrast asthe depth level that is the optimum focal plane; an autofocus adaptationmodule configured for commanding the digital microscope to vary adistance between a focus plane of the microscope and a sample carrierintended to receive the cell sample; and an output unit for outputtingdata indicative of the identified depth level to the autofocusadaptation module, such that the autofocus adaptation module commandsthe digital microscope to set the focus plane at an investigative depthlevel that is based upon the identified depth level.
 28. The autofocuscomputation module according to claim 27, wherein the autofocusadaptation module is configured for commanding the digital microscope toset the focus plane at an investigative depth level that is at theidentified depth level.
 29. The autofocus computation module accordingto claim 27, wherein the autofocus adaptation module is configured toset the focus plane at an investigative depth level corresponding to theidentified depth level shifted by a predetermined value.
 30. Theautofocus computation module according to claim 27, further comprisingthe digital microscope, the digital microscope comprising: an imagingmodule comprising: an optical unit configured for forming a magnifiedimage of the cell sample by conjugating a focus plane and an imageplane; and an image sensor unit positioned in the image plane of theoptical unit; a focus variation module capable of varying a distancebetween the focus plane and the sample carrier; and the autofocusadaptation module cooperating with the focus variation module and theimage sensor unit.
 31. The autofocus computation module according toclaim 27, wherein: the input unit is configured to receive datarepresentative of the series of images captured by performing the depthscan of the cell sample using the microscope by receiving datarepresentative of a series of images captured by performing a depth scanof the cell sample using the microscope, under a first illuminationcondition; the calculation unit is configured to identify one of thedepth levels as being the optimum focal plane for imaging the one ormore entities within the sample using the microscope by identifying oneof the depth levels as being an optimum focal plane for imaging the oneor more entities within the sample using the microscope, under the firstillumination condition; and the output unit is configured to output dataindicative of the identified depth level to the autofocus adaptationmodule, such that the autofocus adaptation module commands the digitalmicroscope to set the focus plane, for imaging the cell sample under asecond illumination condition, at an investigative depth level that isbased upon the identified depth level.
 32. The autofocus computationmodule according to claim 31, wherein: the input unit is configured toreceive data representative of the series of images captured byperforming the depth scan of the cell sample using the microscope byreceiving data representative of a series of images captured byperforming a depth scan of the cell sample using the microscope, underbrightfield illumination conditions; the calculation unit is configuredto identify one of the depth levels as being the optimum focal plane forimaging the one or more entities within the sample using the microscopeby identifying one of the depth levels as being an optimum focal planefor imaging the one or more entities within the sample using themicroscope, under the brightfield illumination conditions; and theoutput unit is configured to output data indicative of the identifieddepth level to the autofocus adaptation module, such that the autofocusadaptation module commands the digital microscope to set the focusplane, for imaging the cell sample under fluorescent illuminationconditions, at an investigative depth level that is based upon theidentified depth level.
 33. The autofocus computation module accordingto claim 31, wherein: the input unit is configured to receive datarepresentative of the series of images captured by performing the depthscan of the cell sample using the microscope by receiving datarepresentative of a series of images captured by performing a depth scanof the cell sample using the microscope, under a first brightfieldillumination condition; the calculation unit is configured to identifyone of the depth levels as being the optimum focal plane for imaging theone or more entities within the sample using the microscope byidentifying one of the depth levels as being an optimum focal plane forimaging the one or more entities within the sample using the microscope,under the first brightfield illumination condition; and the output unitis configured to output data indicative of the identified depth level tothe autofocus adaptation module, such that the autofocus adaptationmodule commands the digital microscope to set the focus plane, forimaging the cell sample under a second brightfield illuminationcondition that is different from the first brightfield illuminationcondition, at an investigative depth level that is based upon theidentified depth level.